Optimal Energy Management of EV Parking Lots Under Peak Load Reduction Based DR Programs Considering Uncertainty

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Ibrahim Sengör (Author) Other; Ozan Erdinç (Author) Other; Baris Yener (Author) Other; Akin Tascikaraoglu (Author) Other; João P. S. Catalão (Author) FEUP

Journal

Title: IEEE Transactions on Sustainable Energy

Vol. 10 No. 3

Pages: 1034-1043

ISSN: 1949-3029

Publisher: IEEE

Indexing

ISI Web of Knowledge - 35 Citations

Scopus - 44 Citations

INSPEC

Other information

Authenticus ID: P-00P-SVQ

DOI: 10.1109/tste.2018.2859186

Abstract (EN): Demand response (DR) programs offer tremendous opportunities to those who have concerns about the future of energy. Since the DR strategies facilitate new technologies to take part in the power systems, the idea of spreading of electric vehicles (EVs) attracts researchers around the world. In this study, an optimal energy management strategy for EV parking lots considering peak load reduction based DR programs is built in stochastic programming framework, denoted by EV parking lot energy management (EV-PLEM). The proposed EV-PLEM aims to maximize the load factor during the daily operation of an EV parking lot taking into account the uncertain behavior of EVs, such as arrival and departure times together with the stochasticity of the remaining state-of-energy of EVs when they reach the parking lot. A set of case studies is conducted to validate the effectiveness of the suggested EV-PLEM concept, and credible results and useful findings are reported for the cases in which the EV-PLEM is implemented.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10